Jatin - Machine learning tutor - New Delhi
1st lesson free
Jatin - Machine learning tutor - New Delhi

Jatin profile and its contact details have been verified by our experts

Jatin

  • Rate R257
  • Response 7h
  • Students

    Number of students Jatin has accompanied since joining Superprof

    3

    Number of students Jatin has accompanied since joining Superprof

Jatin - Machine learning tutor - New Delhi

R257/h

1st lesson free

Contact

1st lesson free

1st lesson free

  • Machine learning

Machine Learning Mentor | Data Science Industry Expert | Transforming Complex Data into Real-World Business Impact

  • Machine learning

Lesson location

About Jatin

With over 5 years of cross-industry expertise spanning healthcare, retail, and tech, I bridge cutting-edge Machine Learning/Data Science techniques with actionable business outcomes. As a Master of Business Analytics graduate and industry practitioner (Telstra, AIHI, ProLearn), I’ve delivered 15%–40% efficiency gains through advanced analytics, deep learning (PyTorch, TensorFlow), and scalable cloud solutions (AWS, Azure, Snowflake). My students don’t just learn algorithms, they master how to apply them to solve real-world problems, from optimizing customer experiences to revolutionizing healthcare diagnostics. Why Learn With Me? Industry-Proven Pedagogy: My curriculum integrates my global experience, like improving medical image classification accuracy by 10% at AIHI or boosting retail KPIs by 15% at Telstra, to teach you how to turn theoretical models into measurable impact. Hands-On, Job-Ready Skills: From GANs (CelebA project) to customer segmentation (Python/SQL) and HPC platforms (NCI GADI), I prioritize tools and projects demanded by top employers. Business Acumen + Technical Depth: With roles like Associate Business Analyst and Executive Assistant, I uniquely teach how to align ML workflows with stakeholder goals, automate reporting (Tableau, Power BI), and communicate insights to non-technical leaders. Ethical, Impact-Driven Focus: My work with NSW Health on Indigenous mental health dashboards and melanoma detection models ensures you’ll learn responsible AI practices for socially impactful careers.

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About the lesson

  • Secondary
  • Matric/GCSE
  • AS Level
  • +13
  • levels :

    Secondary

    Matric/GCSE

    AS Level

    A Level

    BTech

    Adult education

    Undergraduate

    Masters

    Diploma

    Doctorate

    Other

    MBA

    Intermediate

    Advanced

    Professional

    Beginner

  • English

Languages in which the lesson is available :

English

As an educator, my philosophy revolves around “Learn by Breaking Things”, a dynamic blend of hands-on experimentation, industry-aligned case studies, and iterative problem-solving. Here’s how I empower students to master Machine Learning (ML) and Data Science (DS):

1. Teaching Techniques & Methods
Project-Driven Learning: Every concept is tied to a real-world project (e.g., melanoma detection, GANs, customer segmentation) to contextualize theory.
Code-Along Sessions: Live coding demos using Python, PyTorch, and SQL, where students build models with me, not just watch.
Reverse Engineering: Deconstruct complex systems to teach how ML integrates with business workflows.
Socratic Questioning: Foster critical thinking by challenging students to defend their model choices.
Failure Workshops: Break imperfect models (intentionally flawed code/data) and debug collaboratively, because real-world data is messy!

2. Class Structure
Although a fixed class structure is never preferred as every learner has different ways of learning & understanding, but to get an average idea, a typical 90-minute session follows this flow:
Problem Statement (10 mins): Introduce a real industry pain point (e.g., “How do we reduce retail customer churn using clustering?”).
Concept Deep-Dive (25 mins): Theory + visualizations (e.g., how k-means works, pitfalls in high-dimensional data).
Interactive Demo (30 mins): Code a mini-project step-by-step (e.g., segment Telstra’s customer data using Python).
Hackathon-Style Practice (20 mins): Students tweak the code, experiment with parameters, and present results.
Peer Review + Q&A (5 mins): Collaborative feedback and homework preview.

3. Target Audience
My classes are tailored for:
Senior School students including not limited to: 7th-12th aiming to expand academic journey in DS/ML.
College Students (BTech, BSc, MBA) aiming for DS/ML roles.
Early-Career Professionals (1–5 yrs) in IT, healthcare, or analytics seeking upskilling.
Aspiring Entrepreneurs building AI-driven products (Web3/healthtech focus).
Curious Learners, who thrive on structured chaos—rigorous theory paired with creative problem-solving.

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Rates

Rate

  • R257

Package rates

  • 5h: R1285
  • 10h: R2570

online

  • R257/h

free lesson

The free first lesson with Jatin allows you to get to know the tutor and discuss your needs and expectations.

  • 1h

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